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Online Eval Removing service name from Dataframe #3559

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Online Eval Removing service name from Dataframe #3559

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11 changes: 4 additions & 7 deletions .../evaluation_on_cloud/environments/evaluations-built-in/context/online_eval/postprocess.py
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Original file line number Diff line number Diff line change
Expand Up @@ -70,7 +70,7 @@ def log_evaluation_event_single(trace_id, span_id, trace_flags, response_id, eva
_logs.get_logger(__name__).emit(event)


def log_evaluation_event(row) -> None:
def log_evaluation_event(row, service_name) -> None:
"""Log evaluation event."""
if "trace_id" not in row or "span_id" not in row or "evaluation" not in row:
logger.warning("Missing required fields in the row: trace_id, span_id, evaluation")
Expand All @@ -80,14 +80,13 @@ def log_evaluation_event(row) -> None:
trace_flags = TraceFlags(TraceFlags.SAMPLED)
response_id = row.get("gen_ai_response_id", "")
evaluation_results = row.get("evaluation", {})
service_name = row.get("service_name", "evaluation.app")
if isinstance(evaluation_results, dict):
evaluation_results = [evaluation_results]
for evaluation in evaluation_results:
log_evaluation_event_single(trace_id, span_id, trace_flags, response_id, evaluation, service_name)


def get_combined_data(preprocessed_data, evaluated_data, service_name):
def get_combined_data(preprocessed_data, evaluated_data):
"""Combine preprocessed and evaluated data."""
logger.info("Combining preprocessed and evaluated data.")
preprocessed_df = pd.read_json(preprocessed_data, lines=True)
Expand All @@ -97,7 +96,6 @@ def get_combined_data(preprocessed_data, evaluated_data, service_name):
evaluation_data.append(json.loads(line))

preprocessed_df["evaluation"] = evaluation_data
preprocessed_df["service_name"] = service_name
return preprocessed_df


Expand All @@ -108,10 +106,9 @@ def run(args):
f"Service Name: {args['service_name']}"
)
provider = configure_logging(args)
data = get_combined_data(args["preprocessed_data"], args["evaluated_data"],
args["service_name"])
data = get_combined_data(args["preprocessed_data"], args["evaluated_data"])
for _, row in data.iterrows():
log_evaluation_event(row)
log_evaluation_event(row, args["service_name"])
provider.force_flush()


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